In today's electronic commerce markets, exchange of information between vendors and customers must occur in real-time. Vendors need to be able to track the actions and reactions of their potential customers to be able to make decisions as to what products will best suit the customer's needs or interests. For example, as a customer peruses an e-retail website, if the vendor can determine what type of products the customer is looking at, similar products can be quickly displayed on the screen as an additional offer to the customer. All of this must typically happen before the customer logs off from the website, or the vendor's solicitation opportunity will be lost.
“An Operational Data Store (ODS) is an architectural construct that is subject oriented, integrated (i.e., collectively integrated), volatile, current valued, and contains detailed corporate data.” W. H. Inmon, Building the Operational Data Store, second edition, pp. 12-13, John Wiley & Sons, Inc., 1999.
A zero-latency enterprise (ZLE) ODS is a collection of data, the primary purpose of which is to support the time-critical information requirements of the operational functions of an organization. A ZLE ODS is maintained in a state of currency with transaction systems and may be made available for any person who requires access.
The role of any ODS is to provide an environment tuned to information delivery, by containing data at the transaction detail level, coordinated across all relevant source systems, and maintained in a current state.
An ODS presents a convergent/consolidated view of Decision Support System (DSS) and On-Line Transaction Processing (OLTP) operational data on the same sets of tables. This integration transforms operational data, which is application- and clerical-centric, into subject-oriented data containing detailed events on the same sets of tables resulting in an integrated up-to-date view of the business.
To function at the high level of expectation required of a ZLE ODS, detailed event knowledge must be stored. For example, individual transactions such as call detail records, point of sale purchases, Automatic Teller Machine (ATM) transactions, and pay per view purchases are stored at the line item level. Web-based interactions may be stored to enable monitoring of click stream activity, offers extended and results of the offers.
At least one database manufacturer (Oracle Corporation) allows partitioning of tables, in which a table is decomposed into smaller and more manageable pieces called “partitions.” Once partitions are defined, SQL statements can access and manipulate the partitions rather than entire tables or indexes. Partitions may further be subdivided into sub-partitions.